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SignalFire

Staff AI Engineer (Generative AI) - VC Backed Startups

Sorry, this job was removed at 06:15 p.m. (PST) on Tuesday, Nov 11, 2025
In-Office
6 Locations
170K-250K Annually
In-Office
6 Locations
170K-250K Annually

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Join SignalFire’s Talent Network for AI & Machine Learning Roles

🛑 This is not an application for a specific job. Instead, this is a way to get on the radar of VC-backed startups that are actively hiring AI Engineering talent. If you have any questions, please direct inquiries to [email protected].

At SignalFire, we partner with top early-stage startups that are shaping the future of technology. Our portfolio spans 200+ innovative companies across AI, cybersecurity, healthtech, fintech, developer tools, and enterprise SaaS.

We're looking to connect with exceptional Staff AI and Machine Learning engineers who are excited about joining high-growth startups as founding or early team members. By joining SignalFire’s Talent Network, your profile will be shared with our portfolio companies, giving you visibility into exclusive early-stage opportunities that may not be publicly listed.

Who Should Join?

We’re looking for AI engineers who are:
✔ Building cutting-edge AI/ML models and deploying them in production
✔ Excited about joining early-stage startups in transformative industries
✔ Interested in staying connected with SignalFire’s portfolio for future opportunities

Typical roles and responsibilities may include:

  • Developing and deploying machine learning (ML) and deep learning models

  • Building scalable data pipelines for training and inference

  • Working directly with founders to align AI strategies with product roadmaps

  • Researching and implementing state-of-the-art AI methodologies

  • Optimizing RAG pipelines, agent architectures, and LLM-powered systems

Common Qualifications

While each startup has its own hiring criteria, many AI engineering roles in our network look for:

  • 6+ years of experience in AI/ML, deep learning, or applied AI

  • Strong Python skills with frameworks like TensorFlow, PyTorch, or JAX

  • Experience with big data tools (Apache Spark, Kafka, Hadoop) and MLOps platforms

  • Familiarity with cloud environments (AWS, GCP, Azure) and containerization tools (Docker, Kubernetes)

  • Startup experience or an interest in early-stage environments is a plus

💡 Technologies You Might Work With: Python, TensorFlow, PyTorch, JAX, Kubernetes, Docker, MLflow, Kubeflow, FastAPI, SQL, NoSQL, Airflow, Spark, Kafka, Hadoop, AWS (SageMaker, Lambda, S3), GCP (Vertex AI, BigQuery), Azure (ML Studio, Synapse).

What Happens Next?
  1. Submit your application to join SignalFire’s Talent Ecosystem.

  2. We review applications on an ongoing basis to identify strong candidates.

  3. If there’s a match, a SignalFire talent partner or a leader from one of our startups may reach out directly.

  4. No match yet? We’ll keep your profile on file for future AI/ML roles in our portfolio.

HQ

SignalFire San Francisco, California, USA Office

501 2nd St, 100, San Francisco, CA, United States, 94107

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

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